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Jingping Jan
0908-895-931
I am Jingping. I like to find ways to decrease the cost time of processes with any technology, figure out a better method to deal with procedures, and search for a better solution to an unsolved problem. During my master's degree, I researched the hand strength evaluation methods in the contract bridge. The main target of this topic is to find an evaluation method to make the hand strength and the board result more relevant than the hand strength calculated by modern evaluation methods. The power of the hand in the contract bridge is an unsolved problem, and I improved the correlation coefficient between the hand strength and the board result from 0.859 to 0.923. The provided evaluation method can improve the accuracy of the board result prediction from 0.491 to 0.567.
: [email protected]
: zoo868e
: JingPing Jan
Education
National Sun Yat-Sen University
Master of Computer Science
2020 - 2022
National Yunlin University of Science and Technology
Bachelor of Electrical Engineering
2015 - 2020
Skills
C++ Shell Script Python Git Vim
Languages
English — TOEIC 735
Thesis
Hand Strength Evaluation in Bridge Games with the Evolutionary Algorithm • C++/Python/Shell script
Designed various hand-strength evaluation methods and trained the parameters by the genetic algorithm. The research's main target is to find an evaluation method of hand strength that is more relevant to the board result than the modern hand strength evaluation methods. I improved the correlation coefficient between the hand strength and the board result from 0.859 to 0.923, and the provided evaluation method can improve the prediction accuracy of the board result from 0.491 to 0.567.
- C++: Hand strength calculation of each board, create the Share Library to reduce the compile time, use the Makefile to compile automatically, and use the GDB to debug.
- Python: Implement the genetic algorithm and the experiment with the multi-process to speed up the training.
- Shell script: Use Sed to process the data, including the experimental results, and write the script to train the various hand strength evaluation methods.
Jingping Jan
0908-895-931
I am Jingping. I like to find ways to decrease the cost time of processes with any technology, figure out a better method to deal with procedures, and search for a better solution to an unsolved problem. During my master's degree, I researched the hand strength evaluation methods in the contract bridge. The main target of this topic is to find an evaluation method to make the hand strength and the board result more relevant than the hand strength calculated by modern evaluation methods. The power of the hand in the contract bridge is an unsolved problem, and I improved the correlation coefficient between the hand strength and the board result from 0.859 to 0.923. The provided evaluation method can improve the accuracy of the board result prediction from 0.491 to 0.567.
: [email protected]
: zoo868e
: JingPing Jan
Education
National Sun Yat-Sen University
Master of Computer Science
2020 - 2022
National Yunlin University of Science and Technology
Bachelor of Electrical Engineering
2015 - 2020
Skills
C++ Shell Script Python Git Vim
Languages
English — TOEIC 735
Thesis
Hand Strength Evaluation in Bridge Games with the Evolutionary Algorithm • C++/Python/Shell script
Designed various hand-strength evaluation methods and trained the parameters by the genetic algorithm. The research's main target is to find an evaluation method of hand strength that is more relevant to the board result than the modern hand strength evaluation methods. I improved the correlation coefficient between the hand strength and the board result from 0.859 to 0.923, and the provided evaluation method can improve the prediction accuracy of the board result from 0.491 to 0.567.
- C++: Hand strength calculation of each board, create the Share Library to reduce the compile time, use the Makefile to compile automatically, and use the GDB to debug.
- Python: Implement the genetic algorithm and the experiment with the multi-process to speed up the training.
- Shell script: Use Sed to process the data, including the experimental results, and write the script to train the various hand strength evaluation methods.